Deterministic Sampling-Based Motion Planning: Optimality, Complexity, and Performance
This repo contains the code used for results in the paper "Deterministic Sampling-Based Motion Planning: Optimality, Complexity, and Performance" submitted to IJRR in 2015 by Janson, Ichter, and Pavone of Stanford's Autonomous Systems Lab.
All the C code was run through the Open Motion Planning Library (OMPL) at http://ompl.kavrakilab.org/. The MATLAB planning is run through the runFMT.m file. The Julia code is run through the iPython notebook.
- For the Julia Code (kinodynamic planning), the iPython notebooks use the code from https://github.com/schmrlng/MotionPlanning.jl.
- For the C++ code, the Open Motion Planning Library (OMPL) was used and can be found at http://ompl.kavrakilab.org/.
This code is fairly rough and most likely useful as a reference only. It is also subject to changes, bugs, etc. (See disclaimer at https://github.com/schmrlng/MotionPlanning.jl and add a little alpha.)